TinyTorch/tests/module_template/test_capability.py

"""
Capability Tests for Module XX: [Module Name]
Template for testing that the module enables its intended capabilities
"""

import numpy as np
import sys
from pathlib import Path

# Add project root to path
sys.path.insert(0, str(Path(__file__).parent.parent.parent))


class TestModuleCapabilities:
    """Test that the module enables its promised capabilities."""
    
    def test_solves_intended_problem(self):
        """Test the module can solve its primary use case."""
        # Example for Conv2D:
        # from tinytorch.core.spatial import Conv2D
        # 
        # conv = Conv2D(3, 32, kernel_size=3)
        # image = Tensor(np.random.randn(1, 28, 28, 3))
        # features = conv(image)
        # 
        # # Should extract features
        # assert features.shape[-1] == 32  # 32 feature maps
        pass
    
    def test_real_world_scenario(self):
        """Test a real-world usage scenario."""
        # Example for Optimizer:
        # from tinytorch.core.optimizers import Adam
        # from tinytorch.core.layers import Linear
        # 
        # layer = Linear(10, 5)
        # optimizer = Adam(learning_rate=0.001)
        # 
        # # Simulate training step
        # loss = compute_loss()
        # gradients = compute_gradients()
        # optimizer.step(layer.parameters(), gradients)
        # 
        # # Parameters should be updated
        # assert parameters_changed
        pass
    
    def test_performance_acceptable(self):
        """Test that performance is acceptable."""
        # Example:
        # import time
        # 
        # start = time.time()
        # result = expensive_operation()
        # duration = time.time() - start
        # 
        # assert duration < 1.0  # Should complete in under 1 second
        pass